Helping foster youth find a job: a random‐assignment evaluation of an employment assistance programme for emancipating youth
Bibliographic record
Abstract
Abstract A primary task for youth aging out of foster care is finding and maintaining a job. In recognition of the challenges that foster youth face, employment assistance has become an important part of child welfare agencies' efforts to prepare youth for emancipation. The current study uses random assignment to evaluate the impact of an employment assistance programme for foster youth on the rate of employment, income and other self‐sufficiency outcomes among a group of adolescents in substitute care in Kern County, California. Data were collected via multi‐wave, in‐person interviews of 254 foster youth. At the second follow‐up interview, only two‐fifths of the sample report being employed. However, three‐quarters of the sample are either working or attending school, and a quarter reports both working and attending school. Nevertheless, significant minorities report experiencing financial hardships and receiving financial assistance. No statistically significant impacts of the evaluated programme are found on any measured employment or self‐sufficiency outcome. Implications for child welfare policy are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".